Current energy recovery ventilators rely on alternating current (AC) fans. Speed control of AC motors is generally accomplished using tapped transformers, triacs, capacitors or induction coils. These existing solutions present several inconveniences including a limited number of speeds, excessive noise and vibration due to harmonics and reduced energy efficiency. In addition, these techniques also allow for a low number of fan speeds, typically three, which can result in lower ventilation efficiency.
Furthermore, installed ventilation systems often exhibit lower ventilation efficiency than was measured during product testing, resulting in a suboptimal amount of sensible and latent energy being transferred between the exhaust and supply airflows. This is due in part to unbalanced supply and exhaust airflows. A number of factors can lead to this unbalance, including the length and type of the air ducts leading to and from the ventilator and dirty air filters blocking the flow of air. Current ventilation systems do not provide a means for detecting and automatically correcting unbalanced airflows.
Another issue affecting the performance of ventilation systems is the lack of real-time data concerning indoor and outdoor atmospheric conditions to be used in control algorithms. Current systems do not incorporate the means (for example, but not limited to, sensors) necessary for the automated, optimized control of a ventilation system, based on outdoor and indoor environmental conditions.
As a result, there remains a need for a device allowing for fine control of fan speeds and runtime optimization of the airflows entering and exiting a building.